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Record W2066363219 · doi:10.1007/s00005-014-0286-x

Circadian Clocks and Inflammation: Reciprocal Regulation and Shared Mediators

2014· review· en· W2066363219 on OpenAlexafffund
Nicolas Cermakian, Susan Westfall, Silke Kießling

Bibliographic record

VenueArchivum Immunologiae et Therapiae Experimentalis · 2014
Typereview
Languageen
FieldNeuroscience
TopicCircadian rhythm and melatonin
Canadian institutionsMcGill UniversityDouglas Mental Health University Institute
FundersFonds de Recherche du Québec - SantéCanadian Institutes of Health Research
KeywordsCircadian rhythmImmune systemMelatoninBiologyCircadian clockNeuroscienceInflammationEndogenyLight effects on circadian rhythmImmunityImmunologyEndocrinology

Abstract

fetched live from OpenAlex

The immune system is deeply interconnected with the endogenous 24-h oscillators of the circadian system. Indeed, the connection between these two physiological systems occurs at multiple levels and in both directions. On one hand, various aspects of the immune system show daily rhythms, which appear to be essential for healthy immune maintenance and proper immune response. On the other hand, immune responses cause changes in circadian rhythms, disrupting their delicate balance and manifesting in disease. Indeed, immune challenges cause various time-, gene-, and tissue-specific effects on circadian-regulated factors. This article reviews the possible mediators of the cross talk between the circadian clock and the immune system, in particular the inflammatory pathways. The rhythmic expression of cytokines and their receptors, as well as other rhythmically regulated humoral factors such as glucocorticoids, melatonin, leptin, or prostaglandins, could gate the effects of the immune response on the circadian system. In addition, systemic cues such as body temperature and neuronal connections between the brain and peripheral tissues may underlie the immune-circadian communication.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.039
GPT teacher head0.320
Teacher spread0.281 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations91
Published2014
Admission routes2
Has abstractyes

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